{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/11711"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/11711","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Predicting employee voluntary turnover using human resources data","abstract":"The current research attempted to answer the following question: Can voluntary employee turnover be predicted? The study made use of regression analyses to examine the relationship between employee turnover and a range of worker demographics. Data covering 2 592 employees in a South African general insurer formed the basis for the analysis. Several demographic variables (available in the HR management information system), were identified and investigated with the aim to develop a voluntary turnover prediction model. Fourteen variables were identified in the human resources information system to be included for analysis. From 14 potential predictors, the procedure selected only five variables, i.e. cost centre, years of service, performance, age and tenure - family size interaction for inclusion in the regression equation.","abstract_html":"The current research attempted to answer the following question: Can voluntary employee turnover be predicted? The study made use of regression analyses to examine the relationship between employee turnover and a range of worker demographics. Data covering 2 592 employees in a South African general insurer formed the basis for the analysis. Several demographic variables (available in the HR management information system), were identified and investigated with the aim to develop a voluntary turnover prediction model. Fourteen variables were identified in the human resources information system to be included for analysis. From 14 potential predictors, the procedure selected only five variables, i.e. cost centre, years of service, performance, age and tenure - family size interaction for inclusion in the regression equation.","abstract_has_math":false,"creators":["Syce, Chantal"],"institution":"Organisational Psychology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Schlechter, Anton"],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-22T22:22:43Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/11711","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Schlechter, Anton"]},{"key":"dc:creator","label":"Author","values":["Syce, Chantal"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-01-07T13:39:37Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-01-07T13:39:37Z"]},{"key":"dc:date.issued","label":"Date","values":["2012"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Organisational Psychology"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MCom"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/11711"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes bibliographical references."]},{"key":"dc:description.abstract","label":"Abstract","values":["The current research attempted to answer the following question: Can voluntary employee turnover be predicted? The study made use of regression analyses to examine the relationship between employee turnover and a range of worker demographics. Data covering 2 592 employees in a South African general insurer formed the basis for the analysis. Several demographic variables (available in the HR management information system), were identified and investigated with the aim to develop a voluntary turnover prediction model. Fourteen variables were identified in the human resources information system to be included for analysis. From 14 potential predictors, the procedure selected only five variables, i.e. cost centre, years of service, performance, age and tenure - family size interaction for inclusion in the regression equation."]},{"key":"dc:title","label":"Title","values":["Predicting employee voluntary turnover using human resources data"]}]}],"canonical_facts":{"dc:contributor.advisor":["Schlechter, Anton"],"dc:creator":["Syce, Chantal"],"dc:date.accessioned":["2015-01-07T13:39:37Z"],"dc:date.available":["2015-01-07T13:39:37Z"],"dc:date.issued":["2012"],"dc:description":["Includes bibliographical references."],"dc:description.abstract":["The current research attempted to answer the following question: Can voluntary employee turnover be predicted? The study made use of regression analyses to examine the relationship between employee turnover and a range of worker demographics. Data covering 2 592 employees in a South African general insurer formed the basis for the analysis. Several demographic variables (available in the HR management information system), were identified and investigated with the aim to develop a voluntary turnover prediction model. Fourteen variables were identified in the human resources information system to be included for analysis. From 14 potential predictors, the procedure selected only five variables, i.e. cost centre, years of service, performance, age and tenure - family size interaction for inclusion in the regression equation."],"dc:identifier.uri":["http://hdl.handle.net/11427/11711"],"dc:language.iso":["eng"],"dc:publisher.department":["Organisational Psychology"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["Predicting employee voluntary turnover using human resources data"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MCom"]},"updated_at":"2026-07-22T22:22:43Z"}